simulation modeling and analysis of productivity enhancement in
TRANSCRIPT
SIMULATION MODELING AND ANALYSIS OF PRODUCTIVITY
ENHANCEMENT IN MANUFACTURING COMPANY USING ARENA
SOFTWARE
SITI HARTINI BINTI EMBONG @ AB WAHAB
Thesis submitted in fulfillment of the requirements
for the award of the degree of
Bachelor of Engineering in Manufacturing
Faculty of Manufacturing Engineering
UNIVERSITI MALAYSIA PAHANG
JUNE 2013
vii
ABSTRACT
Every manufacturing company wants to improve and adapt their operating system in
order to survive the industry competition. In manufacturing organizations, to improve
their system it might mean to reduce the operating costs that come from the wastes in
production line. By using the ARENA simulation in this study, the productivity
improvement can be experimented without physically affect the real system and reduced
the cost because designing, building, testing, redesigning, rebuilding and retesting can be
an expensive project. This study focus on the flow in the production line processes in
one piston manufacturing company. The existing plant layout was studied and
formulated into ARENA simulation software as well as to enhance the productivity rate
by improving certain parameters. The problems identified in this production line are the
effect of the bottleneck process which resulting some idle time in some workstations and
the increased piston demands from the customers. The data acquired and was translated
into the ARENA simulation software and studied in order to simulate the existing plant
layout design. Hence, the problems occurred in the production line can be seen clearly to
determine room for productivity improvement. New designs are proposed by
constructing several models to acquire the best solution to improve productivity capacity
and meet the forecasting demand of customer. In these proposed models, the parameters
of the actual system are modified accordingly in the terms of material handling such as
human resources, machine cycle time, the number of machines, shape and area of plant
layout. From the simulation results, the significant contribution factor that influenced the
rate of productivity was by adding certain machines to do the same process to cover the
buffer while the material handling did not have a huge effect on the production line.
viii
ABSTRAK
Setiap syarikat pembuatan ingin memperbaiki dan menyesuaikan sistem operasi mereka
untuk terus bersaing dalam industri yang mencabar ini. Bagi organisasi pembuatan,
untuk memperbaiki sistem mereka, ia bermakna, mereka mesti mengurangkan kos
operasi yang tidak bermanfaat. Tumpuan kajian ini adalah untuk mendalami aliran
dalam proses pengeluaran dalam syarikat pembuatan omboh. Susun atur kilang yang
sedia ada dikaji dan ditafsirkan ke dalam perisian simulasi ARENA untuk meningkatkan
kadar produktiviti dengan meningkatkan parameter tertentu. Antara masalah-masalah
yang dikenal pasti dalam pengeluaran ini adalah kesan akibat kesesakn proses tertentu
yang menyebabkan masa terbiar di beberapa stesen kerja dan juga permintaan omboh
sentiasa meningkat daripada pelanggan. Data yang diperolehi akan dikaji dan
diterjemahkan ke dalam perisian simulasi ARENA untuk simulasi reka bentuk susun
atur kilang yang sedia ada. Oleh itu, masalah-masalah yang berlaku dalam proses
pengeluaran dapat dilihat dengan jelas dan kawasan di mana peningkatan produktiviti
yang boleh dibuat dapat ditentukan. Reka bentuk baru dicadangkan dengan membina
beberapa model untuk memperoleh penyelesaian terbaik bagi meningkatkan keupayaan
produktiviti dan memenuhi ramalan permintaan daripada pelanggan. Bagi model
cadangan, parameter sistem sebenar diubahsuai dengan sewajarnya seperti pengendalian
bahan seperti sumber manusia, masa kitaran mesin, bilangan mesin, bentuk dan bidang
susun atur kilang. Daripada laporan simulasi, faktor yang paling mempengaruhi kadar
produktiviti penambahan mesin tertentu untuk melakukan proses yang sama bagi
menampung kesesakan dalam pemprosesan, manakala, faktor pengendalian bahan tidak
memberi kesan yang besar pada kadar pengeluaran produk.
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TABLE OF CONTENTS
Page
EXAMINER APPROVAL DOCUMENT ii
SUPERVISOR’S DECLARATION iii
STUDENT’S DECLARATION iv
DEDICATION v
ACKNOWLEDGEMENTS vi
ABSTRACT vii
ABSTRAK viii
TABLE OF CONTENTS ix
LIST OF TABLES xiii
LIST OF FIGURES xiv
LIST OF ABBREVIATIONS xv
CHAPTER 1 INTRODUCTION
1.1 Preface 1
1.2 Background of Study 1
1.3 Company Background 4
1.4 Project Background 5
1.5 Project Objectives 5
1.6 Project Scopes 6
1.7 Problem Statements 6
CHAPTER 2 LITERATURE REVIEW
2.1 Introduction 8
2.2 Productivity 8
2.3 Material Handling 9
2.4 Facility Layout 10
1 × ENTER (1.5 line spacing)
x
2.5 Simulation 11
2.5.1 Simulation Process 11
2.5.2 Simulation Benefits 14
2.5.3 Disadvantages of Simulation 14
2.6 Application Areas 15
2.7 Simulation Tools 16
2.8 ARENA Simulation Software 17
CHAPTER 3 METHODOLOGY
3.1 Introduction 21
3.2 Project Methodology 21
CHAPTER 4 RESULTS, ANALYSIS AND DISCUSSION
4.1 Introduction 29
4.2 Data Collection 29
4.3 Simulation Model 37
4.3.1 Model 1 (Simulation of Actual Layout Design) 37
4.3.2 Model 2 (Experimental Design) 40
4.3.3 Model 3 (Experimental Design) 41
4.3.4 Model 4 (Experimental Design) 43
4.3.5 Model 5 (Experimental Design) 45
4.3.6 Model 6 (Experimental Design) 47
4.3.7 Model 7 (Experimental Design) 49
4.3.8 Model 8 (Experimental Design) 51
4.3.9 Model 9 (Experimental Design) 53
CHAPTER 5 CONCLUSION AND RECOMMENDATIONS 56
REFERENCES 59
APPENDICES
A1 Gantt Chart For FYP 1 62
A2 Gantt Chart For FYP 2 63
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B1 Production Plant Layout 64
B2 Plant Layout For Piston Machining Cells 65
B3 Capacity Study For Piston Model PN 17 66
B4 Capacity Study for Piston Model CE 17 67
B5 Example of Simulation Parameter (Process & Resource) 68
B6 Example of Simulation Parameter (Queue) 69
B7 Model 1 Animation (1 Hour Run) 70
B8 Model 1 Circuit (1 Hour Run) 71
B9 Model 1 Animation (1 Month Run) 72
B10 Model 1 Circuit (1 Month Run) 73
B11 Model 2 Animation (1 Hour Run) 74
B12 Model 2 Circuit (1 Hour Run) 75
B13 Model 2 Animation (1 Month Run) 76
B14 Model 2 Circuit (1 Month Run) 77
B15 Model 3 Animation (1 Hour Run) 78
B16 Model 3 Circuit (1 Hour Run) 79
B17 Model 3 Animation (1 Month Run) 80
B18 Model 3 Circuit (1 Month Run) 81
B19 Model 4 Animation (1 Hour Run) 82
B20 Model 4 Circuit (1 Hour Run) 83
B21 Model 4 Animation (1 Month Run) 84
B22 Model 4 Circuit (1 Month Run) 85
B23 Model 5 Animation (1 Hour Run) 86
B24 Model 5 Circuit (1 Hour Run) 87
B25 Model 5 Animation (1 Month Run) 88
B26 Model 5 Circuit (1 Month Run) 89
B27 Model 6 Animation (1 Hour Run) 90
B28 Model 6 Circuit (1 Hour Run) 91
B29 Model 6 Animation (1 Month Run) 92
B30 Model 6 Circuit (1 Month Run) 93
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B31 Model 7 Animation (1 Hour Run) 94
B32 Model 7 Circuit (1 Hour Run) 95
B33 Model 7 Animation (1 Month Run) 96
B34 Model 7 Circuit (1 Month Run) 97
B35 Model 8 Animation (1 Hour Run) 98
B36 Model 8 Circuit (1 Hour Run) 99
B37 Model 8 Animation (1 Month Run) 100
B38 Model 8 Circuit (1 Month Run) 101
B39 Model 9 Animation (1 Hour Run) 102
B40 Model 9 Animation (1 Month Run) 103
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LIST OF TABLES
Table No. Page
2.1 Simulation software that available on the market 17
4.1 Piston models for customer ‘NK’ 31
4.2 Comparison between Actual System and Model 1 39
4.3 Comparison between Actual System and Model 2 41
4.4 Comparison between Actual System and Model 3 43
4.5 Comparison between Actual System and Model 4 45
4.6 Comparison between Actual System and Model 5 47
4.7 Comparison between Actual System and Model 6 49
4.8 Comparison between Actual System and Model 7 51
4.9 Comparison between Actual System and Model 8 53
4.10 Comparison between Actual System and Model 9 55
5.1 The comparison of productivity capacity between the models
and actual system
57
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LIST OF FIGURES
Figure No. Page
2.1 The life cycle of a simulation study 13
2.2 Model application window in ARENA simulation software 18
2.3 Example of airport security application model 19
2.4 Example of airport security application model simulation run 19
3.1 Flowchart of project methodology 22
4.1 Features of the piston model 30
4.2 Critical features of the piston 30
4.3 Overall piston production flow 32
4.4 Piston machining process flow in Line 4-5 33
4.5 Machining cell Line 4-4 and 4-5 layout 35
4.6 The view of Model 1 in ARENA simulation 37
4.7 The view of Model 2 in ARENA simulation 40
4.8 The view of Model 3 in ARENA simulation 42
4.9 The view of Model 4 in ARENA simulation 44
4.10 The view of Model 5 in ARENA simulation 46
4.11 The view of Model 6 in ARENA simulation 48
4.12 The view of Model 7 in ARENA simulation 50
4.13 The view of Model 8 in ARENA simulation 52
4.14 The view of Model 9 in ARENA simulation 54
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LIST OF ABBREVIATIONS
BASIC Beginner’s All-purpose Symbolic Instruction Code
C++ C with Classes (programming language)
CAD Computer-aided Design
CAM Computer-aided Manufacturing
CNC Computer Numerical Control
DRB-HICOM Diversified Resources Berhad – The Heavy Industries Corporation of
Malaysia Berhad
FORTRAN The IBM Mathematical Formula Translating System
KPI Key Performance Indicator
OEM Original Equipment Manufacturer
Perodua PERusahaan Otomobil keDUA
Proton Edar PeRusahan OTOmobil Nasional
REM Replacement Equipment Manufacturer
VBA Visual Basic for Applications
WIP Work In Progress
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CHAPTER 1
INTRODUCTION
1.1 PREFACE
This chapter will discuss on the background and rationale of this study. It also
covers on research background which is significantly related to the project objectives,
project scopes, and problem statements.
1.2 BACKGROUND OF STUDY
Nowadays, the automotive industry in Malaysia is recognized as one of the
freshest and provides most steadily growing markets, where it provides the world needs
widely except for America and Continental Europe. Malaysia is stated as the third
South-East Asian auto maker where it produced more than half a million vehicles over a
year assisted by Japan and Korea. Proton Edar (PeRusahaan OTOmobil Nasional),
Perodua (PERusahaan Otomobil keDUA), and DRB-HICOM (Diversified Resources
Berhad – The Heavy Industries Corporation of Malaysia Berhad) are among the most
notable automotive giants in Malaysia industry.
Parallel with the growing and the establishment of the automotive industry, the
automotive component industry also rapidly evolved in order to support and provide the
industry with the automotive partial components. Because of that, the demand of
automotive parts increased tremendously as the most of automotive parts; from small to
large parts, and sophisticated parts have been localized for internal fabrication.
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Consequently, many automotive components suppliers or vendors from Malaysia and
foreign countries have placed a large sum of money to raise plants and support the
automotive manufacturers in Malaysia and entrusted the local vendors to supply the
automotive partial components to them.
As the demand increased in automotive components, the companies are forced to
determine the solution to increase their productivity in order to satisfy the customer
requests. Various existed and fully developed techniques, methodologies and
productivities strategies are available but yet still can be improvised to suit the current
situation in order to determine the ultimate productivity approaches. Of course, as
today's industries competitive, every company must create a quick but efficient decision
to improve and adapt their operating system in order to survive the global challenges and
be on top in their respective discipline. In manufacturing organizations, to improve their
system it might mean to reduce the operating costs that come from the wastes in
production line.
Waste is defined as any activity that does not add any value to the products or
services. The activity that does not add value to the products or services means that the
client is not willing to pay more money for this activity. Waste can be viewed as the
single obstacle that can define a business over time, unless they are identified and
systematically wiped out. Waste elimination is one of the most effective ways to
increase profitability in manufacturing. To eliminate waste, it is important to understand
exactly what waste is and where it exists. While products differ in each factory, the
typical wastes found in manufacturing environments are quite similar.
Generally, there are 7 forms of wastes identified in lean manufacturing;
overproduction, transportation, motion, waiting, processing, inventory and defects. This
paper focus on the two of the forms; motion (people or equipment moving or walking
more than is required to perform the processing) and waiting (waiting for the next
production step). These wastes can be triggered by various factors such as incorrect
plant layouts, lack of proximity of machines and waiting workers, machines and
3
materials. Plant layout design and material handling methods will be the main focal
point of this study due to its large contribution in waste elimination.
The plant layout is a very critical role in running an efficient and cost effective
business. All work areas, production lines, material storage facilities, etc. should be
designed to perform to its highest rate and the corresponding to the shortest cycle time.
When designing a plant layout, it is necessary to take into account all the functions
within the production plant. The pattern must include not only the needs for the present
production levels but should also have provisions for future expansion. This is included
to avoid frequent and costly changes to the design as demand increases.
The efficient layout design is important for reducing the operations and
management costs. The basic objective of layout is to ensure a smooth flow of work,
material, and information through a system. Although, there are several indicators and
objectives to the facility layout problem, the most commonly used objective is the
reduction of material handling.
Material handling is defined as the art and science of moving, packing, and
storing of substances in any form. Material handling is a very vital component of the
design and the needs of a manufacturing facility. Efficient material handling is important
to manufacturing operations. Materials must be unloaded, moved through inspections
and it needs to be properly stored and transferred to and from workstation/centers with a
view towards minimizing the movement and avoiding harm to the merchandise.
These motions do not add value to the product but they do add value to the
production cost. The cost of this being implemented incorrectly could affect the
profitability of the business and also could endanger the employees. In some instances
special handling equipment may be necessary to ensure that the material is handled
properly.
4
Nowadays, simulation studies are widely used for applications in engineering
industry as a tool to increase the capacity of manufacturing and the profit of a company
by avoiding the company making an error in building non-effective layouts and using
wrong approaches. By the simulation also, the company can reduce the time needed to
grow the plants and there is no try-and-error situation because through the simulation, all
the details can be seen and examined thoroughly.
As the proof, the simulation studies are widely used in manufacturing, material
handling, delivery, business operations, and transportation as they has not only assisted
in understanding the details of the processes, but the graphical modeling tools and
animated run like those in ARENA simulation software, also ease the involvement of the
management in the development and the decision making processes.
In this paper, a simulation study using ARENA simulation software was
conducted in order to overcome some of the problems at production line in a
manufacturing factory, particularly the plant layouts, the waiting time at the various
processes due to high cycle time at some stages and material handling.
1.3 COMPANY BACKGROUND
This research will focus on the productivity on one of the automotive component
vendors in Malaysia which produces and supplies car piston parts to the automotive
manufacturers in Malaysia, and also the customer in foreign countries such as Japan and
Europe. The piston is a one of the most important and critical components in car
production which are installed in the engine transmission system, and plays a significant
role as the key contribution to drive the car movement. Its efficiency can be judged by
the movement driven by the combustion in a locomotive.
This piston plant is located in Selangor and has been operated for about 30 years.
They specialize in various kinds of gravity aluminum casting and machining parts. The
plant also fabricates other automotive components such as piston pin, valve housing,
5
pinion housing, mounting brackets, compressor bracket, etc. They produce pistons for
cars, trucks and motorcycles in which the plant runs the fabrication process from the
beginning stage includes melting, casting, heat-treatment, machining, washing, coating
and packaging.
1.4 PROJECT BACKGROUND
This project focuses on the study of the flow in the piston production line
processes in this automotive component vendor company. In this project, the first step to
take is to examine the existing plant layout and the details before applying that layout
design into the application of ARENA simulation software in order to simulate the plant
layout design.
This project is also aiming to develop a process flow simulation model of the
existing plant layout to identify problems occurred in the production line and determine
where the productivity improvement can be realized. The problems and wastes in the
processes are investigated and analyzed. The application of ARENA simulation software
enables the productivity problems occurred in the production floor being highlighted.
Several new plant layout designs are developed to encounter the problems
occurred in the original plant layout and simulated using ARENA simulation software.
From the analysis and the simulation results, a summary of comparison between the
design options is made to determine which option shows the best solution, and then, the
best approach is selected as the best option to be implemented in the chosen company.
1.5 PROJECT OBJECTIVES
1. To study the existing production layout using ARENA simulation software in the
automotive component vendor company that produces piston.
2. To improve the productivity by ameliorate the plant layout and material handling
in the company by simulation using ARENA simulation software.
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1.6 PROJECT SCOPES
This project focuses on the productivity improvement of piston production
processes in the automotive component company. To ensure the objectives are achieved,
some of important elements must be considered. These are:
a) Studying the production processes and present time study for the piston
production processes.
b) Study and applying ARENA simulation software in order to simulate the process
flow in the piston production line.
1.7 PROBLEM STATEMENTS
Nowadays, due to the continuous positive increment in the automotive market,
the automotive component vendors also taking the heat as they are required to increase
their productivity to meet the demands of the automotive manufacturers which are their
clients. The designs and the demands of the components keep changing from time to
time depends on the customer requirement and market situation. These conditions will
lead to the tighten time frame to the production.
In addition, many of automotive vendors racing with each other to improve their
production technology and enhance the production rate as the outcome from the increase
of production cost and competitiveness due to economic globalization. The outcome of
these situations is there are many researches and developments have been performed to
create and modified new equipment/machines, methods, and systems. One of the
methods developed is system modeling by using simulation software, where in this study
will be used ARENA simulation software.
The main problem that occurred in this piston manufacturing line is that they are
struggling to keep up with the demand for piston parts from customer ‘NK’. The
constraint is on the production volume to meet the requirement by the delivery date
fixed by this customer. In the year of 2012, an average of 2,500 sets of piston was
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required per month for all Original Equipment Manufacturer (OEM) models and 1,000
sets for Replacement Equipment Manufacturer (REM) and this was done hardly on time.
Currently, for the January 2013 order, with an increase on the figure of the new car
models introduced, the customer increased the order by added the order for OEM pistons
for model PN 17 to a total number of 7,000 sets, which leading them to increase in
overtime in order to conform to the demand on time. One set of piston has 4 pieces of
pistons; therefore they are required to produce 28,000 pieces of pistons. The forecast of
demand for customer ‘NK’ for the piston model PN 17 in May, June, and July 2013 are
expected to have increment from the current demand which are 15% (8,050 sets), 25%
(8,750 sets), and 27% (8,890 sets).
The piston machining processes also contributed to large total lead time in the
manufacturing processes. It was due to some processes having much longer machining
time than the other. So, the next process would have to wait until the part was done in
the previous stage before proceeding. This situation produced some idle time for
machines and operators at several workstations at the time.
Therefore, in this inquiry, it is important to improve the productivity
enhancement in this production plant up to the level that can fulfill all the customer
needs in not only in the short term but also in the long term. The design must be suitable
for the long term so the company would not cost much money to change the design
frequency. Hence, the simulation modeling analysis by using ARENA simulation
software has been chosen as a method of improvement to the production plant in term of
plant layout, machining processes, and material handling.
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CHAPTER 2
LITERATURE REVIEW
2.1 INTRODUCTION
This chapter will discuss in detail regarding the literature used in order to
conduct and completed this research. The primary reason for the literature reviews is to
identify the right concept and the definition which related to the research title. Each
definition and the concept must be entirely understandable, so when the research is done,
the problems can be discovered easily and the objectives of the research can be
achieved. The resources of this literature review obtained from several secondary
resources such as online journal, books, articles, and related sites.
2.2 PRODUCTIVITY
Productivity can be defined as the measurement of the production line efficiency
of the company. According Aini (2009), productivity is the ratio of outputs (goods and
services) divided by the input (resources, such as labor and capital). It is important to
improve the company‟s productivity, so that the company can remain competitive with
other competitors and be on top of their field.
In order to improve the productivity, the company must firstly improve the
efficiency of their production line. It was essential to minimize or it could, eliminate the
waste, so the goal of improvement can be seen prominently. An organizational survival
was affected by the level of productivity improvement increased through production loss
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reduction and labor efficiency and these efforts can be driven through a host of
productivity improvement initiatives (Longenecker and Standsfield, 2000).
Kaydos (1991) reported that in order to maximize and improve productivity
continuously, the system is required to align their resources to their maximum
capabilities and combined the work study such as scientific analysis, methods, and
logical flow of the process. It is important to generate the process that can meet the level
of productivity and quality required. From a manufacturing standpoint, productivity
improvement is most often translated as: faster cycle time, lower cost, maximized
machine utilization, and also maximized floor space utilization.
2.3 MATERIAL HANDLING
Material handling systems are recognized as one of the basic components in a
manufacturing organization. Material handling can be defined as the activities,
equipment, and procedures that involved in the movement, storage, control and
protection of materials and products throughout the manufacturing processes,
distribution, and disposal. The systems exist for supporting the overall manufacturing
process. It should be understood that part „movement‟ does not add value to the product,
and any unnecessary movement should be eliminated wherever it is possible (Askin and
Standridge, 1993). Material handling equipment encompassed a diverse range of tools,
vehicles, storage units, and appliances and can be categorized as four main categories
such as storage, engineered systems, industrial trucks and bulk material handling.
The storage equipment usually used to hold or buffer materials during downtimes
or when the materials are not being transported. It may refer to pallets, shelves or racks
onto which materials may stacked in an orderly manner while wait for transportation or
consumption. Whilst, the engineered systems are covering a variety of units that work
cohesively to enable storage and transportation and often automated. Good examples of
this system are conveyor and robotic delivery systems.
10
In other hand, industrial trucks are referred as different kinds of transportation
items and vehicles used to move materials and products in material handling systems.
The common type falls under this category are hand trucks, pallet jacks, walkie stackers
and platform trucks. The final category is the bulk material handling equipment. It
referred to the storing, transportation and control of materials in loose bulk form. These
materials included food, fluid, or minerals. The common types of equipment under this
category are conveyor belts, stackers, and hoppers.
For the entire plant, the material handling system acts as the circulating system,
dispatching vital material in all the plant cells. The objective need not be to determine a
minimum cost material handling system, instead, the system that satisfies all the plant
requirements to be effective and efficient manufacturers (Meyers and Stephens, 2000).
2.4 FACILITY LAYOUT
Facilities layout is the arrangement of areas within a facility (Russell and Taylor,
2000). The arrangement is made physically consists of everything needed for the product
or service, including machines, personnel, raw materials, and finished goods. Therefore,
a facility layout design is responsible in minimizes the total cost of products and
compete against competition and increases the factory‟s productivity, business
performance, the effective utilization of manpower, space and infrastructure.
The designed facilities should be flexible to maximize the benefits in an
organization when there are future changes in product design, process design, schedule
design and facility expansion. An effective layout can utilize space and labor efficiently,
facilitate the entry, exit, and placement of material, products, and people, eliminate
bottlenecks, reduce manufacturing cycle time, minimize material handling costs, and
increase productivity, throughput or profitability (Gupta et al., 2004).
Manufacturing facility layouts can be divided into two categories: basic layouts
and hybrid layouts. The basic layouts consist of process, product, and fixed-position
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layouts and the hybrid layouts consist of cellular layouts, flexible manufacturing
systems, and mixed-model assembly lines. Patterns of flow may be viewed from the
perspective of flow within workstations, within the department, and between
departments. There are four general types of general flow pattern: Straight line, U-
shaped, S-shaped, and W-shaped.
2.5 SIMULATION
One of the gurus of simulation Shannon (1975) historically defined simulation as
“the process of designing a model of a real or imaginary system and conducting
experiments with this model for the purpose either of understanding the behavior of the
system or of evaluating various strategies (within the limits imposed by a criterion or set
of criteria) for the operation of the system.” This primitive definition highlights the
general framework of simulation principles and gives a clue of the roadmap that
simulation has gone through within the last century. Each and every word and phrase in
the definition should be further emphasized for exact comprehension of the term
simulation.
The first sentence of the definition mentions the types of systems that simulation
studies can be conducted on. The systems can be “real” or “imaginary”, which means
that there can create a physical facility or a process to be modeled, or the model can be a
modification of the existing system or it can be completely imaginary. The imaginary
systems refer to the ones that are planned as alternatives to existing systems and entirely
original systems.
2.5.1 Simulation Process
As Shannon (1975) stated, simulation is a continuous “process” rather than a
one-time create-and-use application. Especially computer simulation is an iterative
method that includes several stages as Kelton et al., (2004) identified. Firstly, the
simulation study is started by understanding the existing system and identifies the goals
12
of the study. The next step is creating the formulation of the model representation
usually in terms of mathematical models or flowcharts before transferring into modeling
software.
Once a simulation is created, it is necessary to verify the simulation to ensure
right things is done. The following stage is to validate the simulation to familiar subject
that represented the system so that the simulation works in accordance with the
conceptual model faithfully, supporting the validation work with statistical tests can be
of critical importance at this stage. Experimentation with the developed model is done
by designing experiments to identify the critical performance measures to be used with
equal confidence and running these designed experiments by using the computers
effectively.
The last stages take account of analyzing the results, getting an insight of the
results to evaluate the outcomes of the results and to assess the potential benefits.
Finally, documentation is necessary for the inheritance of the work done for other
simulation staff and also to clearly transmit the findings and recommendations to related
management levels with precision and confidence.
The life cycle of a simulation study has also been identified in detail by Balci
(1990). This life cycle has been divided into 10 processes, 10 phases and 13 credibility
assessment stages. Figure 2.1 provides the details of those identifications and the
precedence and succession relations between them.
According to (Sadowski, 1999) a successful simulation project is the one that
delivers useful information at the appropriate time to sustain a meaningful conclusion,
which means that there are three key elements of success in the simulation; decision,
timing and information.
13
Figure 2.1: The life cycle of a simulation study
Source: Balci (1990)
14
2.5.2 Simulation Benefits
Simulation has many benefits for the users as outlined by Banks (2000).
Designing, building, testing, redesigning, rebuilding then retesting can be an expensive
project. Simulations take the building/rebuilding phase out of the loop by using the
model that already created in the design phase. Most of the time, the simulation testing is
cheaper and faster than performing the multiple tests of the design each time.
With simulation, the problems of complex systems can be diagnosed that are
nearly impossible to handle within the actual environment, identify constraints that act
as a bottleneck for operations, visualize the plan using the animation capabilities of the
software used that results in a more presentable design. Simulation is also beneficial to
build consensus among the members of the decision makers and to prepare for changes
by considering the potential “what if” scenarios.
The simulation can be extensively applied as an off-line decision making tool for
aiding the management with production planning issues such as efficient capacity
utilization, sequencing and scheduling and allocation of resources in manufacturing and
production.
2.5.3 Disadvantages of Simulation
Banks (2000) underlines four main disadvantages of simulation:
1) To use the simulation application it requires special training and it is
highly unlikely that models generated by different modelers about the
same system will be the same.
2) The simulation results are difficult to be understood because most
simulation outputs are essentially random variables based on random
inputs, it may be difficult to find out whether an observation is a result of
system interrelationships or randomness.